On multidimensional linear modelling including real uncertainty

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F14%3A86093026" target="_blank" >RIV/61989100:27240/14:86093026 - isvavai.cz</a>
Result on the web
<a href="http://advances.utc.sk/index.php/AEEE/article/view/1143" target="_blank" >http://advances.utc.sk/index.php/AEEE/article/view/1143</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.15598/aeee.v12i5.1143" target="_blank" >10.15598/aeee.v12i5.1143</a>

Result language
angličtina
Original language name
On multidimensional linear modelling including real uncertainty
Original language description
The theoretical background for abstract formalization of vague phenomenon of complex systems is fuzzy set theory. In the paper are defined vague data as specialized fuzzy sets - fuzzy numbers and there is described a fuzzy linear regression model as a fuzzy function with fuzzy numbers as vague regression parameters. To identify the fuzzy coefficients of model the genetic algorithm is used. The linear approximation of vague function together with its possibility area are analytically and graphically expressed. The suitable numerical experiments are performed namely in the task of two-dimensional fuzzy function modelling and the time series fuzzy regression analysis as well.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JB - Sensors, detecting elements, measurement and regulation
OECD FORD branch
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Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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